Overview
We are seeking an experienced consultant with hands-on expertise designing and implementing MCP (Model Context Protocol) server architecture and AI integration frameworks.
This individual will help accelerate the design and deployment of enterprise AI capabilities by building scalable, secure MCP infrastructure that enables LLMs and AI agents to interact with internal systems, APIs, workflows, and enterprise data sources.
The ideal candidate has a strong background in AI architecture, backend engineering, integrations, and modern agentic AI frameworks.
Responsibilities
- Design and implement MCP server architecture for enterprise AI initiatives
- Build secure integrations between AI models and internal/external systems
- Develop tool interfaces, connectors, and orchestration layers for AI agents
- Enable LLM interaction with APIs, databases, SaaS platforms, and business workflows
- Establish authentication, authorization, governance, and observability standards
- Partner with technical and business stakeholders to define scalable AI architecture
- Support rapid prototyping and production deployment of AI-enabled solutions
- Optimize performance, reliability, and security across MCP environments
- Provide architectural guidance on agent frameworks, prompt orchestration, and context management
Required Experience
- Proven experience designing or implementing MCP server environments
- Strong understanding of AI agent architecture and LLM integration patterns
- Experience with APIs, microservices, and backend development
- Experience integrating AI systems with enterprise platforms and data sources
- Knowledge of authentication/security patterns (OAuth, RBAC, API gateways, etc.)
- Hands-on experience with cloud platforms such as Azure, AWS, or GCP
- Strong Python and/or TypeScript/Node.js experience
- Familiarity with vector databases, retrieval systems, and orchestration frameworks
Preferred Experience
- Experience with OpenAI, Anthropic, Azure OpenAI, or similar ecosystems
- Familiarity with LangChain, LangGraph, Semantic Kernel, CrewAI, or similar frameworks
- Experience building production-grade AI copilots or agent workflows
- Enterprise consulting or architecture experience
- Experience operating in regulated or security-conscious environments
Ideal Background
- AI Solutions Architect
- Principal Engineer
- Integration Architect
- AI Platform Engineer
- Agentic AI Consultant
- Backend Architect with AI infrastructure experience
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